A study published in Crystal Growth & Design, "Surface Analysis - From Crystal Structures to Particle Properties," highlights the suite's ability to visualize and quantify chemical and topological information from crystallographic data. Applied to the case study of punch sticking for ibuprofen particles, this approach can reduce the need for expensive trial-and-error methods by providing data-driven guidance for formulators and particle engineers.
Another study in Crystal Growth & Design, "Identifying Possible Slip Systems of Molecular Crystals via a Geometry-Based Procedure," builds on a previously published method (Predicting mechanical properties of crystalline materials through topological analysis ) to identify slip systems in molecular crystals developed by CCDC scientists by using a steric hindrance parameter to quantify molecular overlap as an impediment to slip. This efficient procedure helped to predict the plasticity of energetic materials, supporting better design for these complex products.
A third study in Powder Diffraction, "Predicting Particle Quality Attributes of Organic Crystalline Materials using Particle Informatics," explored the surface properties of crystals of a novel quercetin solvate of dimethylformamide (QDMF). Using CSD-Particle, researchers explored key features of the QDMF particles and validated their findings with experimental methods such as Atomic Force Microscopy (AFM), demonstrating the suite's accuracy and utility.
While the primary application of these tools will be in drug development, their utility extends to the development of agrochemicals, such as pesticides, and other advanced materials and formulated products, where early knowledge of surface properties is advantageous.
These innovations mark a significant advancement in the comprehensive understanding of particle surfaces and their impact on product performance, supporting formulators and particle engineers in making informed, data-driven decisions.
